Scheduling (production processes)

Computer network

Mathematics

Job shop scheduling

Schedule

Dynamic priority scheduling

Operating system

Algorithm

Distributed computing

Mathematical optimization

Workflow management system

Workflow

Artificial intelligence

Workflow technology

Computer science

Quality of service

Cloud computing

Fair-share scheduling

Fuzzy logic

Database

Particle swarm optimization

IEEE Access

The provision of resources and services for scientific workflow applications using a multi-cloud architecture and a pay-per-use rule has recently gained popularity within the cloud computing research domain. This is because workflow applications are computation intensive. Most of the existing studies on workflow scheduling in the cloud mainly focus on finding an ideal makespan or cost. Nevertheless, there are other important quality of service metrics that are of critical concern in workflow scheduling such as reliability and resource utilization. In this respect, this paper proposes a new multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS) for scheduling scientific workflow based on particle swarm optimization (PSO) method. The algorithm minimizes cost and makespan while considering reliability constraint. The coding scheme jointly considers task execution location and data transportation order. Simulation experiments reveal that FR-MOS outperforms the basic MOS over the PSO algorithm.

Scheduling Scientific Workflow Using Multi-Objective Algorithm With Fuzzy Resource Utilization in Multi-Cloud Environment